ArchiTECHt Daily: The practical advice that could prevent deep learning disappointment

I was heartened on Tuesday to read a new report by research firm Altimeter Group that introduces read
ARCHITECHT
ArchiTECHt Daily: The practical advice that could prevent deep learning disappointment
By ARCHITECHT • Issue #8 • View online
I was heartened on Tuesday to read a new report by research firm Altimeter Group that introduces readers to artificial intelligence (as in today’s technology, not the concept) and actually offers some practical advice on how to capitalize on it.  A lot of the talk about AI right now focuses on super-intelligent systems and machines besting humans in complex games (by the way, an AI system called Libratus just crushed a group of professional poker players at Texas Hold'em), but those discussions—while great for page views and certainly interesting—won’t be moving the world’s economic needle. At least not directly.
Rather, it’s mass adoption of AI by mainstream enterprises that’s really going to have a huge impact. And if the rate of adoption, and use cases, of precursor technologies such as cloud computing and big data are any indicator, most enterprises won’t be working on the cutting edge of AI any time soon. Instead, their early use cases will likely be very targeted, rather mundane and, if done correctly, not completely disappointing.
There are three points from the Altimeter Group report that stood out to me. I’ll summarize them:
  1. Data is everything: In order to train systems accurately, you need lots of good, labeled data. Start thinking now about the problems you want to solve, and what data you have (or need) to do that.
  2. Your company is not Google: Tackle low-hanging fruit and optimize existing processes using proven technologies. Don’t think you need an entire AI team or to incorporate it across the business.
  3. There’s more to life than chatbots and digital assistants: Voice-controlled and conversational interfaces have a place, but it’s not everyplace. Depending on the application, your best AI interface might be code with a numerical output.
The report also goes into privacy, governance, the competitive advantage of data, and some other carryover issues from the big data era. That’s understandable if, like me, you view AI as just an evolution of what Hadoop started a decade ago. And those issues certainly have not yet been resolved within most companies, or across broader industries or institutions such as the federal government.
TL;DR: It’s a good, easy to digest report. You should read it.

If you wondering about that human-computer poker tournament. Source: FiveThirtyEight
If you wondering about that human-computer poker tournament. Source: FiveThirtyEight
Around the web: Artificial intelligence
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Around the web: All things data
Source: Revolution Analytics
Source: Revolution Analytics
Around the web: Software, in general
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ARCHITECHT delivers the most interesting news and information about the business impacts of cloud computing, artificial intelligence, and other trends reshaping enterprise IT. Curated by Derrick Harris.

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